The present invention relates generally to web searching, and more particularly to responding to an inquiry in the form of a natural language query received from a client via a network such as the World Wide Web.
The Internet offers access to an enormous amount of information. Search engines (web sites that enable users to search through the vast number of web pages) have become increasingly sophisticated and better at accessing web pages that meet the user's search criteria. Search engines typically perform their searches based on keywords supplied by a user and returns a ranked list of links to relevant web pages. Even if a user inputs a question to a search engine, the search engine will treat some or all of the words of the question as search keywords to search on. Keywords, however, are not always a good indication of the actual question. Thus, the search engine often does not address what the user specifically asks for. Also, people who are not familiar with how a search engine works may find it harder to select the right keywords.
Furthermore, if a user has a question and poses it to a search engine, the list of web pages provided by the search engine may not answer the question. Typically, the user instead has to read through numerous web pages to locate an answer. Thus, it may be burdensome for a user to determine an answer to a question using these types of search engines.
Question-answering (QA) systems provide an alternative to search engines when a user is trying to determine an answer to a question. These systems accept a question as input and typically output a list of answer candidates or a list of web pages containing the answer. Some of these question-answering systems, however, are company specific and have manually crafted questions and answers. Even more established, general domain question-answering systems (i.e., general, not company specific), which often use web crawlers to search web sites and provide an index of the searched sites for answering questions, are limited in their ability to answer a question. For example, current general domain QA systems are time-insensitive. Thus, a question of “Who is the CEO of company XYZ” would, in theory, imply who is the current CEO of that company. The distinction of time, however, is not clearly encoded in current QA systems. The result of such a query, therefore, may be the most recent CEO that the QA system has stored (which may not, in fact, be the current CEO), may be the first CEO of the company XYZ, or may be any of the CEOs of XYZ.
Other QA systems may use Frequently Asked Questions (FAQs), or QA pairs, to answer an inquiry. FAQs, or QA pairs, are common questions and answers about a particular topic displayed on a web page. The topic may be a product or service. The topic may also be about a particular person or organization. These QA systems conventionally employ a small number of FAQs to answer questions. Thus, the questions and answers are structured because there are a limited number of predefined questions and answers stored in a database. Since these QA systems use a small set of structured QA pairs to answer questions, their question answering ability is limited.
Thus, the current question answering systems are limited in their ability to accurately respond to inquiries.